A Multi-Information Propagation Model on Complex Networks

2011 ◽  
Vol 186 ◽  
pp. 302-306 ◽  
Author(s):  
Shu Jing Li ◽  
Feng Jing Shao ◽  
Ren Cheng Sun ◽  
Yi Sui
Keyword(s):  
Complex Networks ◽  
Propagation Rate ◽  
Propagation Model ◽  
Information Propagation ◽  
Influence Propagation ◽  
New Information

Propagation of two kinds of information on complex networks is studied. With assumption that new kind of information is generated after interacting between these two kinds of information, how rate of generating new information and rate of its recovery influence propagation are researched. Experiments show that when rates of propagation of these three kinds of information are same three kinds of information exist after system reaching stable under condition that the rate of generating new information is big. While rates of propagation of these three kinds of information differ a lot, information with big propagation rate exists after system reaching stable. The results could be extended into research of propagation of multi-information on complex networks.

scholarly journals A Bio-Inspired Defensive Rumor Confinement Strategy in Online Social Networks

2021 ◽  
Vol 33 (1) ◽  
pp. 47-70
Author(s):  
Santhoshkumar Srinivasan ◽  
Dhinesh Babu L. D.
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Propagation Model ◽  
Information Propagation ◽  
Control Approach ◽  
Rumor Propagation ◽  
Immunization Strategies ◽  
New Information ◽  
The Individual ◽  
Rumor Control

Online social networks (OSNs) are used to connect people and propagate information around the globe. Along with information propagation, rumors also penetrate across the OSNs in a massive order. Controlling the rumor propagation is utmost important to reduce the damage it causes to society. Educating the individual participants of OSNs is one of the effective ways to control the rumor faster. To educate people in OSNs, this paper proposes a defensive rumor control approach that spreads anti-rumors by the inspiration from the immunization strategies of social insects. In this approach, a new information propagation model is defined to study the defensive nature of true information against rumors. Then, an anti-rumor propagation method with a set of influential spreaders is employed to defend against the rumor. The proposed approach is compared with the existing rumor containment approaches and the results indicate that the proposed approach works well in controlling the rumors.

Modern Diffusion of Products with Complex Network Models

2011 ◽  
pp. 119-133
Author(s):  
Atsushi Tanaka
Keyword(s):  
Complex Networks ◽  
Marketing Strategy ◽  
Complex Network ◽  
Network Models ◽  
Information Propagation ◽  
Multiagent Simulation ◽  
Product Marketing ◽  
Winner Takes All ◽  
Complex Network Models

In this chapter, some important matters of complex networks and their models are reviewed shortly, and then the modern diffusion of products under the information propagation using multiagent simulation is discussed. The remarkable phenomena like “Winner-Takes-All” and “Chasm” can be observed, and one product marketing strategy is also proposed.

Information propagation based on historical memory

2019 ◽  
Vol 30 (12) ◽  
pp. 2050005 ◽  
Author(s):  
Fuzhong Nian ◽  
Anhui Cong ◽  
Rendong Liu
Keyword(s):  
Network Model ◽  
Critical Path ◽  
Historical Memory ◽  
Propagation Model ◽  
Information Propagation ◽  
Core Network ◽  
Memory Strength ◽  
Network Information ◽  
Long Time ◽  
With Memory

This paper aims at the phenomenon of information selective propagation based on historical memory. A network model with memory strength and edge strength is established. The information propagation model with memory-clustering ability is designed with SIR model. And unsupervised learning is introduced to modify the performance. Based on the new network model, the core network and critical path that play a key role in the information propagation are found through the K-shell decomposition method. The research shows that the memory network contains an inertial channel for information propagation, it makes information propagation smooth. And information is selectively propagated in the new network, information is more inclined to propagate between nodes with powerful memory strength and close connections, in other words, people are more willing to propagate information to old friends who have been in contact for a long time instead of new friends.

A two-layer SIR information propagation model with heterogeneity based on coupled network

2019 ◽  
Vol 76 (3) ◽  
pp. 1657-1679 ◽  
Author(s):  
Tongrang Fan ◽  
Wanting Qin ◽  
Wenbin Zhao ◽  
Feng Wu ◽  
Jianmin Wang
Keyword(s):  
Propagation Model ◽  
Information Propagation

Evolution of node impact based on secondary propagation

2019 ◽  
Vol 34 (02) ◽  
pp. 2050027
Author(s):  
Fuzhong Nian ◽  
Kai Gao
Keyword(s):  
Real Life ◽  
Propagation Model ◽  
Information Propagation ◽  
Actual Situation ◽  
Scale Free Network ◽  
Scale Free ◽  
Initial Stage ◽  
Free Network ◽  
Three Stages ◽  
Stable Stage

In real life, the propagation ability of the information disseminator is one of the important factors which is determined to propagate information. The influence of the node, which is altered with time, is proposed to reflect the propagation ability of the information disseminator for the significance of the information propagation in the actual situation in this paper. Therefore, the influence of the node is divided into the high-impact node and the low-impact node. Furthermore, the SSIR information propagation model is proposed and the dynamic BA scale-free network is constructed to carry out evolution of node impact based on secondary propagation experiments. The experiment results indicate three stages, including the initial stage, the rapidly rising stage and the stable stage. The propagation details of the different messages are distinct. However, the trend of propagation is similar.

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